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  Mixing and Merging for Spoken Document Retrieval (1998) [12 citations — 3 self]

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by Mark Sanderson, Fabio Crestani
in Proceedings of SIGIR
http://dis.shef.ac.uk/mark/cv/publications/papers/my_papers/Euro_DL_2nd.ps.gz
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Abstract:

Abstract. This paper describes a number of experiments that explored the issues surrounding the retrieval of spoken documents. Two such issues were examined. First, attempting to find the best use of speech recogniser output to produce the highest retrieval effectiveness. Second, investigating the potential problems of retrieving from a so-called "mixed collection ", i.e. one that contains documents from both a speech recognition system (producing many errors) and from hand transcription (producing presumably near perfect documents). The result of the first part of the work found that merging the transcripts of multiple recognisers showed most promise. The investigation in the second part showed how the term weighting scheme used in a retrieval system was important in determining whether the system was affected detrimentally when retrieving from a mixed collection. 1

Citations

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18 Measuring the effects of data corruption on information retrieval – Mittendorf, Schauble - 1996
13 Short queries, natural language and spoken document retrieval: Experiments at Glasgow University – Crestani, Sanderson, et al. - 1998
11 AT&T at TREC-6: SDR track – Singhal, Choi, et al. - 1997
9 Video Mail Retrieval using Voice: An overview of the Cambridge/Olivetti retrieval system – Brown, Foote, et al. - 1994
9 Experiments in spoken document retrieval at CMU – Siegler, Witbrock, et al. - 1998
5 Retrieval of Spoken Documents: First Experiences. Departmental Research – Crestani, Sanderson - 1997
5 System for information retrieval experiments (SIRE). Unpublished paper – Sanderson - 1996
2 The design and application of an acoustic front-end for use in speech interfaces – Gerber - 1997
2 The use of recurrent networks in continuos speech reognition – Robinson, Hochberg, et al. - 1996
2 Lenght normalisation in degraded text collections – Singhal, Salton, et al. - 1995
2 Results of applying probabilistic IR to OCR – Taghva, Borsack, et al. - 1994